Overview

Brought to you by YData

Dataset statistics

Number of variables21
Number of observations187531
Missing cells1074764
Missing cells (%)27.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory30.0 MiB
Average record size in memory168.0 B

Variable types

Numeric2
Text9
Categorical8
Unsupported2

Alerts

Status has constant value "Ready to Move" Constant
Transaction is highly imbalanced (59.6%) Imbalance
Ownership is highly imbalanced (74.4%) Imbalance
Description has 3023 (1.6%) missing values Missing
Price (in rupees) has 17665 (9.4%) missing values Missing
Carpet Area has 80673 (43.0%) missing values Missing
Floor has 7077 (3.8%) missing values Missing
Furnishing has 2897 (1.5%) missing values Missing
facing has 70233 (37.5%) missing values Missing
overlooking has 81436 (43.4%) missing values Missing
Society has 109678 (58.5%) missing values Missing
Balcony has 48935 (26.1%) missing values Missing
Car Parking has 103357 (55.1%) missing values Missing
Ownership has 65517 (34.9%) missing values Missing
Super Area has 107685 (57.4%) missing values Missing
Dimensions has 187531 (100.0%) missing values Missing
Plot Area has 187531 (100.0%) missing values Missing
Price (in rupees) is highly skewed (γ1 = 177.1133698) Skewed
Index is uniformly distributed Uniform
Index has unique values Unique
Dimensions is an unsupported type, check if it needs cleaning or further analysis Unsupported
Plot Area is an unsupported type, check if it needs cleaning or further analysis Unsupported

Reproduction

Analysis started2025-09-15 04:59:09.865953
Analysis finished2025-09-15 04:59:20.834484
Duration10.97 seconds
Software versionydata-profiling vv4.16.1
Download configurationconfig.json

Variables

Index
Real number (ℝ)

Uniform  Unique 

Distinct187531
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean93765
Minimum0
Maximum187530
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size1.4 MiB
2025-09-15T10:29:20.937164image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile9376.5
Q146882.5
median93765
Q3140647.5
95-th percentile178153.5
Maximum187530
Range187530
Interquartile range (IQR)93765

Descriptive statistics

Standard deviation54135.681
Coefficient of variation (CV)0.57735489
Kurtosis-1.2
Mean93765
Median Absolute Deviation (MAD)46883
Skewness0
Sum1.7583844 × 1010
Variance2.930672 × 109
MonotonicityStrictly increasing
2025-09-15T10:29:21.088628image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1
 
< 0.1%
125013 1
 
< 0.1%
125015 1
 
< 0.1%
125016 1
 
< 0.1%
125017 1
 
< 0.1%
125018 1
 
< 0.1%
125019 1
 
< 0.1%
125020 1
 
< 0.1%
125021 1
 
< 0.1%
125022 1
 
< 0.1%
Other values (187521) 187521
> 99.9%
ValueCountFrequency (%)
0 1
< 0.1%
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
ValueCountFrequency (%)
187530 1
< 0.1%
187529 1
< 0.1%
187528 1
< 0.1%
187527 1
< 0.1%
187526 1
< 0.1%
187525 1
< 0.1%
187524 1
< 0.1%
187523 1
< 0.1%
187522 1
< 0.1%
187521 1
< 0.1%

Title
Text

Distinct32446
Distinct (%)17.3%
Missing0
Missing (%)0.0%
Memory size1.4 MiB
2025-09-15T10:29:21.352895image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length168
Median length124
Mean length61.897702
Min length29

Characters and Unicode

Total characters11607738
Distinct characters79
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20487 ?
Unique (%)10.9%

Sample

1st row1 BHK Ready to Occupy Flat for sale in Srushti Siddhi Mangal Murti Complex Bhiwandi
2nd row2 BHK Ready to Occupy Flat for sale in Dosti Vihar Pokhran Road
3rd row2 BHK Ready to Occupy Flat for sale in Sunrise by Kalpataru Kolshet Road
4th row1 BHK Ready to Occupy Flat for sale Kasheli
5th row2 BHK Ready to Occupy Flat for sale in TenX Habitat Raymond Realty Pokhran Road
ValueCountFrequency (%)
for 187534
 
8.2%
sale 187534
 
8.2%
flat 187508
 
8.1%
to 186628
 
8.1%
bhk 186615
 
8.1%
ready 186612
 
8.1%
occupy 186610
 
8.1%
in 108582
 
4.7%
3 82217
 
3.6%
2 80970
 
3.5%
Other values (14988) 719905
31.3%
2025-09-15T10:29:21.747618image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2114375
18.2%
a 1172416
 
10.1%
e 645368
 
5.6%
t 568540
 
4.9%
o 566068
 
4.9%
l 515312
 
4.4%
r 496664
 
4.3%
c 442666
 
3.8%
y 436497
 
3.8%
i 316826
 
2.7%
Other values (69) 4333006
37.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 11607738
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2114375
18.2%
a 1172416
 
10.1%
e 645368
 
5.6%
t 568540
 
4.9%
o 566068
 
4.9%
l 515312
 
4.4%
r 496664
 
4.3%
c 442666
 
3.8%
y 436497
 
3.8%
i 316826
 
2.7%
Other values (69) 4333006
37.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 11607738
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2114375
18.2%
a 1172416
 
10.1%
e 645368
 
5.6%
t 568540
 
4.9%
o 566068
 
4.9%
l 515312
 
4.4%
r 496664
 
4.3%
c 442666
 
3.8%
y 436497
 
3.8%
i 316826
 
2.7%
Other values (69) 4333006
37.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 11607738
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2114375
18.2%
a 1172416
 
10.1%
e 645368
 
5.6%
t 568540
 
4.9%
o 566068
 
4.9%
l 515312
 
4.4%
r 496664
 
4.3%
c 442666
 
3.8%
y 436497
 
3.8%
i 316826
 
2.7%
Other values (69) 4333006
37.3%

Description
Text

Missing 

Distinct65634
Distinct (%)35.6%
Missing3023
Missing (%)1.6%
Memory size1.4 MiB
2025-09-15T10:29:21.965072image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length3422
Median length1587
Mean length377.70668
Min length5

Characters and Unicode

Total characters69689904
Distinct characters103
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique62686 ?
Unique (%)34.0%

Sample

1st rowBhiwandi, Thane has an attractive 1 BHK Flat for sale. The property is ideally located in a strategic location in Srushti Siddhi Mangal Murti Complex township. This flat for resale is a choice property. This apartment ready to move in the Bhiwandi is available for an attractive price of INR 42 Lac. You will find it unfurnished.
2nd rowOne can find this stunning 2 BHK flat for sale in Pokhran Road, Thane. It enjoys an excellent location within the Dosti Vihar. This flat for resale is a choice property. This ready to move flat in Pokhran Road can be availed at a reasonable price of INR 98 Lac. This semi-furnished flat is strategically designed with all the amenities to enhance the living experience. The property is strategically placed near prominent places as near singhaniya school which make for the smooth living of residents.
3rd rowUp for immediate sale is a 2 BHK apartment in Kolshet Road, Thane. Don't miss this bargain flat for sale. Situated in the Sunrise By Kalpataru township, it has a prime location. This flat for resale has a desirable location. You can buy this ready to move flat in Kolshet Road at a reasonable price of INR 1.40 Cr. This unfurnished flat is strategically designed with all the amenities to enhance the living experience. Landmarks near the apartment include pokhran road no 2.
4th rowThis beautiful 1 BHK Flat is available for sale in Kasheli, Thane. This flat for resale has a desirable location. This ready to move flat is offered at an economical price of INR 25 Lac. You will find it unfurnished.
5th rowThis lovely 2 BHK Flat in Pokhran Road, Thane is up for sale. This flat is situated in the Tenx Habitat Raymond Realty township and is equipped with premium facilities. This flat is an attractive property for resale. You can buy this ready to move flat in Pokhran Road at a reasonable price of INR 1.60 Cr. You will find it unfurnished. Some of the landmarks in the vicinity include pokhran road 2.
ValueCountFrequency (%)
is 653794
 
5.3%
flat 542721
 
4.4%
this 542421
 
4.4%
in 522929
 
4.3%
the 521136
 
4.3%
for 451080
 
3.7%
a 320506
 
2.6%
of 318987
 
2.6%
to 277296
 
2.3%
sale 237502
 
1.9%
Other values (31280) 7866348
64.2%
2025-09-15T10:29:22.381953image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
12053677
17.3%
a 6309174
 
9.1%
e 5617920
 
8.1%
i 4773206
 
6.8%
t 4120896
 
5.9%
r 3489051
 
5.0%
s 3427620
 
4.9%
o 3336188
 
4.8%
n 3104122
 
4.5%
l 2964529
 
4.3%
Other values (93) 20493521
29.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 69689904
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
12053677
17.3%
a 6309174
 
9.1%
e 5617920
 
8.1%
i 4773206
 
6.8%
t 4120896
 
5.9%
r 3489051
 
5.0%
s 3427620
 
4.9%
o 3336188
 
4.8%
n 3104122
 
4.5%
l 2964529
 
4.3%
Other values (93) 20493521
29.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 69689904
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
12053677
17.3%
a 6309174
 
9.1%
e 5617920
 
8.1%
i 4773206
 
6.8%
t 4120896
 
5.9%
r 3489051
 
5.0%
s 3427620
 
4.9%
o 3336188
 
4.8%
n 3104122
 
4.5%
l 2964529
 
4.3%
Other values (93) 20493521
29.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 69689904
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
12053677
17.3%
a 6309174
 
9.1%
e 5617920
 
8.1%
i 4773206
 
6.8%
t 4120896
 
5.9%
r 3489051
 
5.0%
s 3427620
 
4.9%
o 3336188
 
4.8%
n 3104122
 
4.5%
l 2964529
 
4.3%
Other values (93) 20493521
29.4%
Distinct1561
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.4 MiB
2025-09-15T10:29:22.612352image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length14
Median length7
Mean length7.8351313
Min length5

Characters and Unicode

Total characters1469330
Distinct characters23
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique218 ?
Unique (%)0.1%

Sample

1st row42 Lac
2nd row98 Lac
3rd row1.40 Cr
4th row25 Lac
5th row1.60 Cr
ValueCountFrequency (%)
lac 112568
29.3%
cr 65279
17.0%
call 9684
 
2.5%
for 9684
 
2.5%
price 9684
 
2.5%
85 5264
 
1.4%
65 4229
 
1.1%
60 3870
 
1.0%
70 3801
 
1.0%
35 3369
 
0.9%
Other values (1516) 157314
40.9%
2025-09-15T10:29:22.950195image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
375062
25.5%
c 122252
 
8.3%
a 122252
 
8.3%
L 112568
 
7.7%
r 84647
 
5.8%
. 78625
 
5.4%
5 78308
 
5.3%
C 74963
 
5.1%
1 59931
 
4.1%
2 54540
 
3.7%
Other values (13) 306182
20.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1469330
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
375062
25.5%
c 122252
 
8.3%
a 122252
 
8.3%
L 112568
 
7.7%
r 84647
 
5.8%
. 78625
 
5.4%
5 78308
 
5.3%
C 74963
 
5.1%
1 59931
 
4.1%
2 54540
 
3.7%
Other values (13) 306182
20.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1469330
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
375062
25.5%
c 122252
 
8.3%
a 122252
 
8.3%
L 112568
 
7.7%
r 84647
 
5.8%
. 78625
 
5.4%
5 78308
 
5.3%
C 74963
 
5.1%
1 59931
 
4.1%
2 54540
 
3.7%
Other values (13) 306182
20.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1469330
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
375062
25.5%
c 122252
 
8.3%
a 122252
 
8.3%
L 112568
 
7.7%
r 84647
 
5.8%
. 78625
 
5.4%
5 78308
 
5.3%
C 74963
 
5.1%
1 59931
 
4.1%
2 54540
 
3.7%
Other values (13) 306182
20.8%

Price (in rupees)
Real number (ℝ)

Missing  Skewed 

Distinct10958
Distinct (%)6.5%
Missing17665
Missing (%)9.4%
Infinite0
Infinite (%)0.0%
Mean7583.7719
Minimum0
Maximum6700000
Zeros11
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size1.4 MiB
2025-09-15T10:29:23.076786image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3000
Q14297
median6034
Q39450
95-th percentile16111
Maximum6700000
Range6700000
Interquartile range (IQR)5153

Descriptive statistics

Standard deviation27241.706
Coefficient of variation (CV)3.5921051
Kurtosis35039.49
Mean7583.7719
Median Absolute Deviation (MAD)2034
Skewness177.11337
Sum1.288225 × 109
Variance7.4211054 × 108
MonotonicityNot monotonic
2025-09-15T10:29:23.215366image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4000 2463
 
1.3%
5000 2286
 
1.2%
10000 2273
 
1.2%
3200 1479
 
0.8%
18000 1420
 
0.8%
6522 1241
 
0.7%
6000 1203
 
0.6%
6667 1076
 
0.6%
11056 953
 
0.5%
5333 909
 
0.5%
Other values (10948) 154563
82.4%
(Missing) 17665
 
9.4%
ValueCountFrequency (%)
0 11
< 0.1%
1 3
 
< 0.1%
4 2
 
< 0.1%
7 1
 
< 0.1%
17 1
 
< 0.1%
21 1
 
< 0.1%
48 1
 
< 0.1%
80 1
 
< 0.1%
86 1
 
< 0.1%
95 1
 
< 0.1%
ValueCountFrequency (%)
6700000 1
< 0.1%
4500000 2
< 0.1%
4041600 1
< 0.1%
3450000 1
< 0.1%
2669100 1
< 0.1%
1200000 1
< 0.1%
322727 1
< 0.1%
291667 1
< 0.1%
282609 1
< 0.1%
197183 1
< 0.1%
Distinct81
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.4 MiB
2025-09-15T10:29:23.387784image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length7.9829148
Min length3

Characters and Unicode

Total characters1497044
Distinct characters25
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowthane
2nd rowthane
3rd rowthane
4th rowthane
5th rowthane
ValueCountFrequency (%)
new-delhi 27599
14.7%
bangalore 24030
12.8%
kolkata 22380
11.9%
gurgaon 20070
10.7%
ahmedabad 12750
 
6.8%
hyderabad 12300
 
6.6%
chennai 10500
 
5.6%
jaipur 8490
 
4.5%
greater-noida 4710
 
2.5%
faridabad 3840
 
2.0%
Other values (71) 40862
21.8%
2025-09-15T10:29:23.637093image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 274999
18.4%
e 132316
 
8.8%
n 117101
 
7.8%
d 105261
 
7.0%
r 100152
 
6.7%
o 83220
 
5.6%
h 81005
 
5.4%
l 80636
 
5.4%
i 78566
 
5.2%
g 76825
 
5.1%
Other values (15) 366963
24.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1497044
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 274999
18.4%
e 132316
 
8.8%
n 117101
 
7.8%
d 105261
 
7.0%
r 100152
 
6.7%
o 83220
 
5.6%
h 81005
 
5.4%
l 80636
 
5.4%
i 78566
 
5.2%
g 76825
 
5.1%
Other values (15) 366963
24.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1497044
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 274999
18.4%
e 132316
 
8.8%
n 117101
 
7.8%
d 105261
 
7.0%
r 100152
 
6.7%
o 83220
 
5.6%
h 81005
 
5.4%
l 80636
 
5.4%
i 78566
 
5.2%
g 76825
 
5.1%
Other values (15) 366963
24.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1497044
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 274999
18.4%
e 132316
 
8.8%
n 117101
 
7.8%
d 105261
 
7.0%
r 100152
 
6.7%
o 83220
 
5.6%
h 81005
 
5.4%
l 80636
 
5.4%
i 78566
 
5.2%
g 76825
 
5.1%
Other values (15) 366963
24.5%

Carpet Area
Text

Missing 

Distinct2758
Distinct (%)2.6%
Missing80673
Missing (%)43.0%
Memory size1.4 MiB
2025-09-15T10:29:23.872020image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length11
Median length9
Mean length8.5526025
Min length6

Characters and Unicode

Total characters913914
Distinct characters31
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique809 ?
Unique (%)0.8%

Sample

1st row500 sqft
2nd row473 sqft
3rd row779 sqft
4th row530 sqft
5th row635 sqft
ValueCountFrequency (%)
sqft 100428
47.0%
sqyrd 5526
 
2.6%
1000 5288
 
2.5%
900 4651
 
2.2%
1300 3457
 
1.6%
1600 2753
 
1.3%
600 2227
 
1.0%
1500 2154
 
1.0%
950 1941
 
0.9%
1250 1675
 
0.8%
Other values (2472) 83616
39.1%
2025-09-15T10:29:24.215689image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 127945
14.0%
106858
11.7%
s 106848
11.7%
q 106848
11.7%
t 100429
11.0%
f 100428
11.0%
1 64297
7.0%
5 41382
 
4.5%
7 22572
 
2.5%
8 21012
 
2.3%
Other values (21) 115295
12.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 913914
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 127945
14.0%
106858
11.7%
s 106848
11.7%
q 106848
11.7%
t 100429
11.0%
f 100428
11.0%
1 64297
7.0%
5 41382
 
4.5%
7 22572
 
2.5%
8 21012
 
2.3%
Other values (21) 115295
12.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 913914
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 127945
14.0%
106858
11.7%
s 106848
11.7%
q 106848
11.7%
t 100429
11.0%
f 100428
11.0%
1 64297
7.0%
5 41382
 
4.5%
7 22572
 
2.5%
8 21012
 
2.3%
Other values (21) 115295
12.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 913914
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 127945
14.0%
106858
11.7%
s 106848
11.7%
q 106848
11.7%
t 100429
11.0%
f 100428
11.0%
1 64297
7.0%
5 41382
 
4.5%
7 22572
 
2.5%
8 21012
 
2.3%
Other values (21) 115295
12.6%

Status
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing615
Missing (%)0.3%
Memory size1.4 MiB
Ready to Move
186916 

Length

Max length13
Median length13
Mean length13
Min length13

Characters and Unicode

Total characters2429908
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowReady to Move
2nd rowReady to Move
3rd rowReady to Move
4th rowReady to Move
5th rowReady to Move

Common Values

ValueCountFrequency (%)
Ready to Move 186916
99.7%
(Missing) 615
 
0.3%

Length

2025-09-15T10:29:24.344442image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-09-15T10:29:24.581038image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
ready 186916
33.3%
to 186916
33.3%
move 186916
33.3%

Most occurring characters

ValueCountFrequency (%)
e 373832
15.4%
373832
15.4%
o 373832
15.4%
R 186916
7.7%
a 186916
7.7%
d 186916
7.7%
y 186916
7.7%
t 186916
7.7%
M 186916
7.7%
v 186916
7.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2429908
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 373832
15.4%
373832
15.4%
o 373832
15.4%
R 186916
7.7%
a 186916
7.7%
d 186916
7.7%
y 186916
7.7%
t 186916
7.7%
M 186916
7.7%
v 186916
7.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2429908
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 373832
15.4%
373832
15.4%
o 373832
15.4%
R 186916
7.7%
a 186916
7.7%
d 186916
7.7%
y 186916
7.7%
t 186916
7.7%
M 186916
7.7%
v 186916
7.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2429908
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 373832
15.4%
373832
15.4%
o 373832
15.4%
R 186916
7.7%
a 186916
7.7%
d 186916
7.7%
y 186916
7.7%
t 186916
7.7%
M 186916
7.7%
v 186916
7.7%

Floor
Text

Missing 

Distinct947
Distinct (%)0.5%
Missing7077
Missing (%)3.8%
Memory size1.4 MiB
2025-09-15T10:29:24.684917image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length24
Median length10
Mean length10.833243
Min length1

Characters and Unicode

Total characters1954902
Distinct characters28
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique136 ?
Unique (%)0.1%

Sample

1st row10 out of 11
2nd row3 out of 22
3rd row10 out of 29
4th row1 out of 3
5th row20 out of 42
ValueCountFrequency (%)
out 180405
25.0%
of 180405
25.0%
4 61758
 
8.6%
3 46154
 
6.4%
2 41709
 
5.8%
5 32950
 
4.6%
1 32937
 
4.6%
10 18204
 
2.5%
6 15944
 
2.2%
7 14888
 
2.1%
Other values (70) 96677
13.4%
2025-09-15T10:29:24.919021image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
541577
27.7%
o 373300
19.1%
u 192759
 
9.9%
t 180767
 
9.2%
f 180405
 
9.2%
1 105730
 
5.4%
4 70703
 
3.6%
2 69197
 
3.5%
3 58181
 
3.0%
5 40294
 
2.1%
Other values (18) 141989
 
7.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1954902
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
541577
27.7%
o 373300
19.1%
u 192759
 
9.9%
t 180767
 
9.2%
f 180405
 
9.2%
1 105730
 
5.4%
4 70703
 
3.6%
2 69197
 
3.5%
3 58181
 
3.0%
5 40294
 
2.1%
Other values (18) 141989
 
7.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1954902
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
541577
27.7%
o 373300
19.1%
u 192759
 
9.9%
t 180767
 
9.2%
f 180405
 
9.2%
1 105730
 
5.4%
4 70703
 
3.6%
2 69197
 
3.5%
3 58181
 
3.0%
5 40294
 
2.1%
Other values (18) 141989
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1954902
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
541577
27.7%
o 373300
19.1%
u 192759
 
9.9%
t 180767
 
9.2%
f 180405
 
9.2%
1 105730
 
5.4%
4 70703
 
3.6%
2 69197
 
3.5%
3 58181
 
3.0%
5 40294
 
2.1%
Other values (18) 141989
 
7.3%

Transaction
Categorical

Imbalance 

Distinct4
Distinct (%)< 0.1%
Missing83
Missing (%)< 0.1%
Memory size1.4 MiB
Resale
144172 
New Property
42565 
Other
 
709
Rent/Lease
 
2

Length

Max length12
Median length6
Mean length7.3587182
Min length5

Characters and Unicode

Total characters1379377
Distinct characters19
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowResale
2nd rowResale
3rd rowResale
4th rowResale
5th rowResale

Common Values

ValueCountFrequency (%)
Resale 144172
76.9%
New Property 42565
 
22.7%
Other 709
 
0.4%
Rent/Lease 2
 
< 0.1%
(Missing) 83
 
< 0.1%

Length

2025-09-15T10:29:25.043790image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-09-15T10:29:25.152787image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
resale 144172
62.7%
new 42565
 
18.5%
property 42565
 
18.5%
other 709
 
0.3%
rent/lease 2
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
e 374189
27.1%
R 144174
 
10.5%
s 144174
 
10.5%
a 144174
 
10.5%
l 144172
 
10.5%
r 85839
 
6.2%
t 43276
 
3.1%
w 42565
 
3.1%
42565
 
3.1%
P 42565
 
3.1%
Other values (9) 171684
12.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1379377
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 374189
27.1%
R 144174
 
10.5%
s 144174
 
10.5%
a 144174
 
10.5%
l 144172
 
10.5%
r 85839
 
6.2%
t 43276
 
3.1%
w 42565
 
3.1%
42565
 
3.1%
P 42565
 
3.1%
Other values (9) 171684
12.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1379377
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 374189
27.1%
R 144174
 
10.5%
s 144174
 
10.5%
a 144174
 
10.5%
l 144172
 
10.5%
r 85839
 
6.2%
t 43276
 
3.1%
w 42565
 
3.1%
42565
 
3.1%
P 42565
 
3.1%
Other values (9) 171684
12.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1379377
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 374189
27.1%
R 144174
 
10.5%
s 144174
 
10.5%
a 144174
 
10.5%
l 144172
 
10.5%
r 85839
 
6.2%
t 43276
 
3.1%
w 42565
 
3.1%
42565
 
3.1%
P 42565
 
3.1%
Other values (9) 171684
12.4%

Furnishing
Categorical

Missing 

Distinct3
Distinct (%)< 0.1%
Missing2897
Missing (%)1.5%
Memory size1.4 MiB
Semi-Furnished
88318 
Unfurnished
76154 
Furnished
20162 

Length

Max length14
Median length11
Mean length12.216623
Min length9

Characters and Unicode

Total characters2255604
Distinct characters14
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowUnfurnished
2nd rowSemi-Furnished
3rd rowUnfurnished
4th rowUnfurnished
5th rowUnfurnished

Common Values

ValueCountFrequency (%)
Semi-Furnished 88318
47.1%
Unfurnished 76154
40.6%
Furnished 20162
 
10.8%
(Missing) 2897
 
1.5%

Length

2025-09-15T10:29:25.277784image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-09-15T10:29:25.371001image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
semi-furnished 88318
47.8%
unfurnished 76154
41.2%
furnished 20162
 
10.9%

Most occurring characters

ValueCountFrequency (%)
e 272952
12.1%
i 272952
12.1%
n 260788
11.6%
u 184634
8.2%
r 184634
8.2%
s 184634
8.2%
h 184634
8.2%
d 184634
8.2%
F 108480
 
4.8%
S 88318
 
3.9%
Other values (4) 328944
14.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2255604
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 272952
12.1%
i 272952
12.1%
n 260788
11.6%
u 184634
8.2%
r 184634
8.2%
s 184634
8.2%
h 184634
8.2%
d 184634
8.2%
F 108480
 
4.8%
S 88318
 
3.9%
Other values (4) 328944
14.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2255604
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 272952
12.1%
i 272952
12.1%
n 260788
11.6%
u 184634
8.2%
r 184634
8.2%
s 184634
8.2%
h 184634
8.2%
d 184634
8.2%
F 108480
 
4.8%
S 88318
 
3.9%
Other values (4) 328944
14.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2255604
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 272952
12.1%
i 272952
12.1%
n 260788
11.6%
u 184634
8.2%
r 184634
8.2%
s 184634
8.2%
h 184634
8.2%
d 184634
8.2%
F 108480
 
4.8%
S 88318
 
3.9%
Other values (4) 328944
14.6%

facing
Categorical

Missing 

Distinct8
Distinct (%)< 0.1%
Missing70233
Missing (%)37.5%
Memory size1.4 MiB
East
54741 
North - East
24220 
North
16533 
West
8574 
South
 
4694
Other values (3)
8536 

Length

Max length12
Median length4
Mean length6.3973469
Min length4

Characters and Unicode

Total characters750396
Distinct characters14
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowEast
2nd rowEast
3rd rowWest
4th rowEast
5th rowEast

Common Values

ValueCountFrequency (%)
East 54741
29.2%
North - East 24220
 
12.9%
North 16533
 
8.8%
West 8574
 
4.6%
South 4694
 
2.5%
North - West 3843
 
2.0%
South - East 2622
 
1.4%
South -West 2071
 
1.1%
(Missing) 70233
37.5%

Length

2025-09-15T10:29:25.496505image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-09-15T10:29:25.627376image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
east 81583
45.1%
north 44596
24.7%
30685
 
17.0%
west 14488
 
8.0%
south 9387
 
5.2%

Most occurring characters

ValueCountFrequency (%)
t 150054
20.0%
s 96071
12.8%
E 81583
10.9%
a 81583
10.9%
63441
8.5%
o 53983
 
7.2%
h 53983
 
7.2%
N 44596
 
5.9%
r 44596
 
5.9%
- 32756
 
4.4%
Other values (4) 47750
 
6.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 750396
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
t 150054
20.0%
s 96071
12.8%
E 81583
10.9%
a 81583
10.9%
63441
8.5%
o 53983
 
7.2%
h 53983
 
7.2%
N 44596
 
5.9%
r 44596
 
5.9%
- 32756
 
4.4%
Other values (4) 47750
 
6.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 750396
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
t 150054
20.0%
s 96071
12.8%
E 81583
10.9%
a 81583
10.9%
63441
8.5%
o 53983
 
7.2%
h 53983
 
7.2%
N 44596
 
5.9%
r 44596
 
5.9%
- 32756
 
4.4%
Other values (4) 47750
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 750396
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
t 150054
20.0%
s 96071
12.8%
E 81583
10.9%
a 81583
10.9%
63441
8.5%
o 53983
 
7.2%
h 53983
 
7.2%
N 44596
 
5.9%
r 44596
 
5.9%
- 32756
 
4.4%
Other values (4) 47750
 
6.4%

overlooking
Categorical

Missing 

Distinct19
Distinct (%)< 0.1%
Missing81436
Missing (%)43.4%
Memory size1.4 MiB
Main Road
32193 
Garden/Park, Main Road
27238 
Garden/Park
23077 
Garden/Park, Pool, Main Road
12413 
Pool, Garden/Park, Main Road
3615 
Other values (14)
7559 

Length

Max length43
Median length30
Mean length16.24577
Min length4

Characters and Unicode

Total characters1723595
Distinct characters21
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st rowGarden/Park
2nd rowGarden/Park
3rd rowGarden/Park, Main Road
4th rowGarden/Park, Main Road
5th rowGarden/Park

Common Values

ValueCountFrequency (%)
Main Road 32193
 
17.2%
Garden/Park, Main Road 27238
 
14.5%
Garden/Park 23077
 
12.3%
Garden/Park, Pool, Main Road 12413
 
6.6%
Pool, Garden/Park, Main Road 3615
 
1.9%
Garden/Park, Pool 2880
 
1.5%
Main Road, Garden/Park, Pool 1359
 
0.7%
Pool, Main Road 1136
 
0.6%
Pool 1012
 
0.5%
Main Road, Garden/Park 666
 
0.4%
Other values (9) 506
 
0.3%
(Missing) 81436
43.4%

Length

2025-09-15T10:29:25.772806image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
main 78690
31.2%
road 78690
31.2%
garden/park 71738
28.5%
pool 22916
 
9.1%
not 7
 
< 0.1%
available 7
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
a 300870
17.5%
n 150428
 
8.7%
d 150428
 
8.7%
145953
 
8.5%
r 143476
 
8.3%
o 124529
 
7.2%
P 94654
 
5.5%
i 78697
 
4.6%
M 78690
 
4.6%
R 78690
 
4.6%
Other values (11) 377180
21.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1723595
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 300870
17.5%
n 150428
 
8.7%
d 150428
 
8.7%
145953
 
8.5%
r 143476
 
8.3%
o 124529
 
7.2%
P 94654
 
5.5%
i 78697
 
4.6%
M 78690
 
4.6%
R 78690
 
4.6%
Other values (11) 377180
21.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1723595
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 300870
17.5%
n 150428
 
8.7%
d 150428
 
8.7%
145953
 
8.5%
r 143476
 
8.3%
o 124529
 
7.2%
P 94654
 
5.5%
i 78697
 
4.6%
M 78690
 
4.6%
R 78690
 
4.6%
Other values (11) 377180
21.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1723595
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 300870
17.5%
n 150428
 
8.7%
d 150428
 
8.7%
145953
 
8.5%
r 143476
 
8.3%
o 124529
 
7.2%
P 94654
 
5.5%
i 78697
 
4.6%
M 78690
 
4.6%
R 78690
 
4.6%
Other values (11) 377180
21.9%

Society
Text

Missing 

Distinct10376
Distinct (%)13.3%
Missing109678
Missing (%)58.5%
Memory size1.4 MiB
2025-09-15T10:29:25.986338image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length59
Median length48
Mean length16.441434
Min length3

Characters and Unicode

Total characters1280015
Distinct characters71
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5147 ?
Unique (%)6.6%

Sample

1st rowSrushti Siddhi Mangal Murti Complex
2nd rowDosti Vihar
3rd rowSunrise by Kalpataru
4th rowTenX Habitat Raymond Realty
5th rowVirat Aangan
ValueCountFrequency (%)
apartment 8714
 
4.4%
apartments 4144
 
2.1%
city 3543
 
1.8%
park 3537
 
1.8%
heights 2986
 
1.5%
dlf 2778
 
1.4%
town 2646
 
1.3%
residency 2187
 
1.1%
garden 2030
 
1.0%
2 1985
 
1.0%
Other values (6532) 165229
82.7%
2025-09-15T10:29:26.339956image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 142599
 
11.1%
121926
 
9.5%
e 98550
 
7.7%
r 82421
 
6.4%
i 71063
 
5.6%
t 70176
 
5.5%
n 68936
 
5.4%
s 49131
 
3.8%
o 42461
 
3.3%
m 41142
 
3.2%
Other values (61) 491610
38.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1280015
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 142599
 
11.1%
121926
 
9.5%
e 98550
 
7.7%
r 82421
 
6.4%
i 71063
 
5.6%
t 70176
 
5.5%
n 68936
 
5.4%
s 49131
 
3.8%
o 42461
 
3.3%
m 41142
 
3.2%
Other values (61) 491610
38.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1280015
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 142599
 
11.1%
121926
 
9.5%
e 98550
 
7.7%
r 82421
 
6.4%
i 71063
 
5.6%
t 70176
 
5.5%
n 68936
 
5.4%
s 49131
 
3.8%
o 42461
 
3.3%
m 41142
 
3.2%
Other values (61) 491610
38.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1280015
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 142599
 
11.1%
121926
 
9.5%
e 98550
 
7.7%
r 82421
 
6.4%
i 71063
 
5.6%
t 70176
 
5.5%
n 68936
 
5.4%
s 49131
 
3.8%
o 42461
 
3.3%
m 41142
 
3.2%
Other values (61) 491610
38.4%

Bathroom
Categorical

Distinct11
Distinct (%)< 0.1%
Missing828
Missing (%)0.4%
Memory size1.4 MiB
2
93007 
3
55781 
1
18654 
4
15600 
5
 
3343
Other values (6)
 
318

Length

Max length4
Median length1
Mean length1.0006374
Min length1

Characters and Unicode

Total characters186822
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row2
3rd row2
4th row1
5th row2

Common Values

ValueCountFrequency (%)
2 93007
49.6%
3 55781
29.7%
1 18654
 
9.9%
4 15600
 
8.3%
5 3343
 
1.8%
6 209
 
0.1%
> 10 35
 
< 0.1%
7 35
 
< 0.1%
10 14
 
< 0.1%
8 14
 
< 0.1%
(Missing) 828
 
0.4%

Length

2025-09-15T10:29:26.465225image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2 93007
49.8%
3 55781
29.9%
1 18654
 
10.0%
4 15600
 
8.4%
5 3343
 
1.8%
6 209
 
0.1%
10 49
 
< 0.1%
35
 
< 0.1%
7 35
 
< 0.1%
8 14
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
2 93007
49.8%
3 55781
29.9%
1 18703
 
10.0%
4 15600
 
8.4%
5 3343
 
1.8%
6 209
 
0.1%
0 49
 
< 0.1%
> 35
 
< 0.1%
35
 
< 0.1%
7 35
 
< 0.1%
Other values (2) 25
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 186822
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2 93007
49.8%
3 55781
29.9%
1 18703
 
10.0%
4 15600
 
8.4%
5 3343
 
1.8%
6 209
 
0.1%
0 49
 
< 0.1%
> 35
 
< 0.1%
35
 
< 0.1%
7 35
 
< 0.1%
Other values (2) 25
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 186822
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2 93007
49.8%
3 55781
29.9%
1 18703
 
10.0%
4 15600
 
8.4%
5 3343
 
1.8%
6 209
 
0.1%
0 49
 
< 0.1%
> 35
 
< 0.1%
35
 
< 0.1%
7 35
 
< 0.1%
Other values (2) 25
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 186822
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2 93007
49.8%
3 55781
29.9%
1 18703
 
10.0%
4 15600
 
8.4%
5 3343
 
1.8%
6 209
 
0.1%
0 49
 
< 0.1%
> 35
 
< 0.1%
35
 
< 0.1%
7 35
 
< 0.1%
Other values (2) 25
 
< 0.1%

Balcony
Categorical

Missing 

Distinct11
Distinct (%)< 0.1%
Missing48935
Missing (%)26.1%
Memory size1.4 MiB
2
51809 
1
49219 
3
27111 
4
9420 
5
 
841
Other values (6)
 
196

Length

Max length4
Median length1
Mean length1.00057
Min length1

Characters and Unicode

Total characters138675
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
2 51809
27.6%
1 49219
26.2%
3 27111
14.5%
4 9420
 
5.0%
5 841
 
0.4%
6 132
 
0.1%
> 10 22
 
< 0.1%
7 14
 
< 0.1%
10 13
 
< 0.1%
8 13
 
< 0.1%
(Missing) 48935
26.1%

Length

2025-09-15T10:29:26.590555image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2 51809
37.4%
1 49219
35.5%
3 27111
19.6%
4 9420
 
6.8%
5 841
 
0.6%
6 132
 
0.1%
10 35
 
< 0.1%
22
 
< 0.1%
7 14
 
< 0.1%
8 13
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
2 51809
37.4%
1 49254
35.5%
3 27111
19.6%
4 9420
 
6.8%
5 841
 
0.6%
6 132
 
0.1%
0 35
 
< 0.1%
> 22
 
< 0.1%
22
 
< 0.1%
7 14
 
< 0.1%
Other values (2) 15
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 138675
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2 51809
37.4%
1 49254
35.5%
3 27111
19.6%
4 9420
 
6.8%
5 841
 
0.6%
6 132
 
0.1%
0 35
 
< 0.1%
> 22
 
< 0.1%
22
 
< 0.1%
7 14
 
< 0.1%
Other values (2) 15
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 138675
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2 51809
37.4%
1 49254
35.5%
3 27111
19.6%
4 9420
 
6.8%
5 841
 
0.6%
6 132
 
0.1%
0 35
 
< 0.1%
> 22
 
< 0.1%
22
 
< 0.1%
7 14
 
< 0.1%
Other values (2) 15
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 138675
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2 51809
37.4%
1 49254
35.5%
3 27111
19.6%
4 9420
 
6.8%
5 841
 
0.6%
6 132
 
0.1%
0 35
 
< 0.1%
> 22
 
< 0.1%
22
 
< 0.1%
7 14
 
< 0.1%
Other values (2) 15
 
< 0.1%

Car Parking
Text

Missing 

Distinct229
Distinct (%)0.3%
Missing103357
Missing (%)55.1%
Memory size1.4 MiB
2025-09-15T10:29:26.700144image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length12
Median length9
Mean length8.8736189
Min length6

Characters and Unicode

Total characters746928
Distinct characters21
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique122 ?
Unique (%)0.1%

Sample

1st row1 Open
2nd row1 Covered
3rd row1 Covered
4th row1 Covered
5th row1 Open
ValueCountFrequency (%)
covered 72648
43.2%
1 63618
37.8%
2 17258
 
10.3%
open 11526
 
6.8%
10 871
 
0.5%
3 585
 
0.3%
34 573
 
0.3%
402 318
 
0.2%
8 215
 
0.1%
4 172
 
0.1%
Other values (148) 564
 
0.3%
2025-09-15T10:29:26.918099image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 156822
21.0%
84174
11.3%
C 72648
9.7%
o 72648
9.7%
v 72648
9.7%
r 72648
9.7%
d 72648
9.7%
1 64739
8.7%
, 21194
 
2.8%
2 17740
 
2.4%
Other values (11) 39019
 
5.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 746928
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 156822
21.0%
84174
11.3%
C 72648
9.7%
o 72648
9.7%
v 72648
9.7%
r 72648
9.7%
d 72648
9.7%
1 64739
8.7%
, 21194
 
2.8%
2 17740
 
2.4%
Other values (11) 39019
 
5.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 746928
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 156822
21.0%
84174
11.3%
C 72648
9.7%
o 72648
9.7%
v 72648
9.7%
r 72648
9.7%
d 72648
9.7%
1 64739
8.7%
, 21194
 
2.8%
2 17740
 
2.4%
Other values (11) 39019
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 746928
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 156822
21.0%
84174
11.3%
C 72648
9.7%
o 72648
9.7%
v 72648
9.7%
r 72648
9.7%
d 72648
9.7%
1 64739
8.7%
, 21194
 
2.8%
2 17740
 
2.4%
Other values (11) 39019
 
5.2%

Ownership
Categorical

Imbalance  Missing 

Distinct4
Distinct (%)< 0.1%
Missing65517
Missing (%)34.9%
Memory size1.4 MiB
Freehold
112229 
Leasehold
 
5285
Co-operative Society
 
3431
Power Of Attorney
 
1069

Length

Max length20
Median length8
Mean length8.459603
Min length8

Characters and Unicode

Total characters1032190
Distinct characters26
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowFreehold
2nd rowFreehold
3rd rowCo-operative Society
4th rowCo-operative Society
5th rowCo-operative Society

Common Values

ValueCountFrequency (%)
Freehold 112229
59.8%
Leasehold 5285
 
2.8%
Co-operative Society 3431
 
1.8%
Power Of Attorney 1069
 
0.6%
(Missing) 65517
34.9%

Length

2025-09-15T10:29:27.027414image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-09-15T10:29:27.137300image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
freehold 112229
88.0%
leasehold 5285
 
4.1%
co-operative 3431
 
2.7%
society 3431
 
2.7%
power 1069
 
0.8%
of 1069
 
0.8%
attorney 1069
 
0.8%

Most occurring characters

ValueCountFrequency (%)
e 247459
24.0%
o 129945
12.6%
r 117798
11.4%
h 117514
11.4%
l 117514
11.4%
d 117514
11.4%
F 112229
10.9%
t 9000
 
0.9%
a 8716
 
0.8%
i 6862
 
0.7%
Other values (16) 47639
 
4.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1032190
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 247459
24.0%
o 129945
12.6%
r 117798
11.4%
h 117514
11.4%
l 117514
11.4%
d 117514
11.4%
F 112229
10.9%
t 9000
 
0.9%
a 8716
 
0.8%
i 6862
 
0.7%
Other values (16) 47639
 
4.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1032190
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 247459
24.0%
o 129945
12.6%
r 117798
11.4%
h 117514
11.4%
l 117514
11.4%
d 117514
11.4%
F 112229
10.9%
t 9000
 
0.9%
a 8716
 
0.8%
i 6862
 
0.7%
Other values (16) 47639
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1032190
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 247459
24.0%
o 129945
12.6%
r 117798
11.4%
h 117514
11.4%
l 117514
11.4%
d 117514
11.4%
F 112229
10.9%
t 9000
 
0.9%
a 8716
 
0.8%
i 6862
 
0.7%
Other values (16) 47639
 
4.6%

Super Area
Text

Missing 

Distinct2976
Distinct (%)3.7%
Missing107685
Missing (%)57.4%
Memory size1.4 MiB
2025-09-15T10:29:27.371877image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length14
Median length9
Mean length8.7352278
Min length6

Characters and Unicode

Total characters697473
Distinct characters33
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique830 ?
Unique (%)1.0%

Sample

1st row680 sqft
2nd row575 sqft
3rd row600 sqft
4th row1165 sqft
5th row844 sqft
ValueCountFrequency (%)
sqft 75406
47.2%
sqyrd 3547
 
2.2%
1100 2599
 
1.6%
1332 2111
 
1.3%
1500 2018
 
1.3%
500 1681
 
1.1%
1000 1361
 
0.9%
1450 1023
 
0.6%
1300 1007
 
0.6%
1850 941
 
0.6%
Other values (2756) 67998
42.6%
2025-09-15T10:29:27.745438image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
79846
11.4%
s 79827
11.4%
q 79826
11.4%
t 75408
10.8%
f 75406
10.8%
0 72558
10.4%
1 70386
10.1%
5 33951
 
4.9%
2 20240
 
2.9%
3 19067
 
2.7%
Other values (23) 90958
13.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 697473
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
79846
11.4%
s 79827
11.4%
q 79826
11.4%
t 75408
10.8%
f 75406
10.8%
0 72558
10.4%
1 70386
10.1%
5 33951
 
4.9%
2 20240
 
2.9%
3 19067
 
2.7%
Other values (23) 90958
13.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 697473
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
79846
11.4%
s 79827
11.4%
q 79826
11.4%
t 75408
10.8%
f 75406
10.8%
0 72558
10.4%
1 70386
10.1%
5 33951
 
4.9%
2 20240
 
2.9%
3 19067
 
2.7%
Other values (23) 90958
13.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 697473
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
79846
11.4%
s 79827
11.4%
q 79826
11.4%
t 75408
10.8%
f 75406
10.8%
0 72558
10.4%
1 70386
10.1%
5 33951
 
4.9%
2 20240
 
2.9%
3 19067
 
2.7%
Other values (23) 90958
13.0%

Dimensions
Unsupported

Missing  Rejected  Unsupported 

Missing187531
Missing (%)100.0%
Memory size1.4 MiB

Plot Area
Unsupported

Missing  Rejected  Unsupported 

Missing187531
Missing (%)100.0%
Memory size1.4 MiB

Interactions

2025-09-15T10:29:18.730456image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-09-15T10:29:18.475343image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-09-15T10:29:18.849205image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-09-15T10:29:18.607142image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Correlations

2025-09-15T10:29:27.825810image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
BalconyBathroomFurnishingIndexOwnershipPrice (in rupees)Transactionfacingoverlooking
Balcony1.0000.2860.1510.1250.1420.0140.0550.1550.114
Bathroom0.2861.0000.1130.1360.1100.0000.1040.0910.138
Furnishing0.1510.1131.0000.1470.0750.0000.1420.2290.111
Index0.1250.1360.1471.0000.208-0.1670.1430.2230.201
Ownership0.1420.1100.0750.2081.0000.0170.0540.1070.179
Price (in rupees)0.0140.0000.000-0.1670.0171.0000.0000.0000.000
Transaction0.0550.1040.1420.1430.0540.0001.0000.0760.155
facing0.1550.0910.2290.2230.1070.0000.0761.0000.208
overlooking0.1140.1380.1110.2010.1790.0000.1550.2081.000

Missing values

2025-09-15T10:29:19.182637image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
A simple visualization of nullity by column.
2025-09-15T10:29:19.663468image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2025-09-15T10:29:20.441013image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

IndexTitleDescriptionAmount(in rupees)Price (in rupees)locationCarpet AreaStatusFloorTransactionFurnishingfacingoverlookingSocietyBathroomBalconyCar ParkingOwnershipSuper AreaDimensionsPlot Area
001 BHK Ready to Occupy Flat for sale in Srushti Siddhi Mangal Murti Complex BhiwandiBhiwandi, Thane has an attractive 1 BHK Flat for sale. The property is ideally located in a strategic location in Srushti Siddhi Mangal Murti Complex township. This flat for resale is a choice property. This apartment ready to move in the Bhiwandi is available for an attractive price of INR 42 Lac. You will find it unfurnished.42 Lac6000.0thane500 sqftReady to Move10 out of 11ResaleUnfurnishedNaNNaNSrushti Siddhi Mangal Murti Complex12NaNNaNNaNNaNNaN
112 BHK Ready to Occupy Flat for sale in Dosti Vihar Pokhran RoadOne can find this stunning 2 BHK flat for sale in Pokhran Road, Thane. It enjoys an excellent location within the Dosti Vihar. This flat for resale is a choice property. This ready to move flat in Pokhran Road can be availed at a reasonable price of INR 98 Lac. This semi-furnished flat is strategically designed with all the amenities to enhance the living experience. The property is strategically placed near prominent places as near singhaniya school which make for the smooth living of residents.98 Lac13799.0thane473 sqftReady to Move3 out of 22ResaleSemi-FurnishedEastGarden/ParkDosti Vihar2NaN1 OpenFreeholdNaNNaNNaN
222 BHK Ready to Occupy Flat for sale in Sunrise by Kalpataru Kolshet RoadUp for immediate sale is a 2 BHK apartment in Kolshet Road, Thane. Don't miss this bargain flat for sale. Situated in the Sunrise By Kalpataru township, it has a prime location. This flat for resale has a desirable location. You can buy this ready to move flat in Kolshet Road at a reasonable price of INR 1.40 Cr. This unfurnished flat is strategically designed with all the amenities to enhance the living experience. Landmarks near the apartment include pokhran road no 2.1.40 Cr17500.0thane779 sqftReady to Move10 out of 29ResaleUnfurnishedEastGarden/ParkSunrise by Kalpataru2NaN1 CoveredFreeholdNaNNaNNaN
331 BHK Ready to Occupy Flat for sale KasheliThis beautiful 1 BHK Flat is available for sale in Kasheli, Thane. This flat for resale has a desirable location. This ready to move flat is offered at an economical price of INR 25 Lac. You will find it unfurnished.25 LacNaNthane530 sqftReady to Move1 out of 3ResaleUnfurnishedNaNNaNNaN11NaNNaNNaNNaNNaN
442 BHK Ready to Occupy Flat for sale in TenX Habitat Raymond Realty Pokhran RoadThis lovely 2 BHK Flat in Pokhran Road, Thane is up for sale. This flat is situated in the Tenx Habitat Raymond Realty township and is equipped with premium facilities. This flat is an attractive property for resale. You can buy this ready to move flat in Pokhran Road at a reasonable price of INR 1.60 Cr. You will find it unfurnished. Some of the landmarks in the vicinity include pokhran road 2.1.60 Cr18824.0thane635 sqftReady to Move20 out of 42ResaleUnfurnishedWestGarden/Park, Main RoadTenX Habitat Raymond Realty2NaN1 CoveredCo-operative SocietyNaNNaNNaN
551 BHK Ready to Occupy Flat for sale in Virat Aangan TitwalaCreatively planned and constructed is a 1 BHK flat for sale in Titwala, Thane. It is housed in the well-planned Virat Aangan township in an advantageous location. This flat is available as a resale property. You can buy this ready to move flat in Titwala at a reasonable price of INR 45 Lac. The flat is uniquely designed to enhance the living style. It is unfurnished, studded with all the basic facilities.45 Lac6618.0thaneNaNReady to Move2 out of 7ResaleUnfurnishedEastGarden/Park, Main RoadVirat Aangan11NaNCo-operative Society680 sqftNaNNaN
661 BHK Ready to Occupy Flat for sale MumbraThis magnificent 1 BHK Flat is available for sale in Mumbra, Thane. This premium flat is available for resale at an unbelievable price, so, grab it before it's gone! Located in Mumbra, this ready to move apartment is sold at a fair selling price of INR 16.5 Lac. The spacious apartment is unfurnished.16.5 Lac2538.0thane550 sqftReady to Move4 out of 5ResaleUnfurnishedNaNNaNNaN1NaNNaNNaNNaNNaNNaN
771 BHK Ready to Occupy Flat for sale KalwaCreatively planned and constructed is a 1 BHK flat for sale in Kalwa, Thane. This flat is an attractive property for resale. This ready to move flat located in Kalwa is available for purchase at a fair price of INR 60 Lac. This furnished flat is strategically designed with all the amenities to enhance the living experience.60 Lac10435.0thaneNaNReady to MoveGround out of 7ResaleFurnishedNaNNaNNaN1NaNNaNNaN575 sqftNaNNaN
881 BHK Ready to Occupy Flat for sale KalwaDiscover this immaculate 1 BHK flat for sale at the pristine Kalwa in Thane. This apartment is a property of choice for resale. This ready to move flat is offered at an economical price of INR 60 Lac. This contemporary apartment is furnished. Some of the landmarks in the vicinity include the property is a 1 bhk flat located at manisha nagar heart of thane.::::centralized location near thane and new mumbai. near swimming pool,hotel, collage and school, market,hospital.60 Lac10000.0thaneNaNReady to MoveGround out of 2ResaleFurnishedNaNNaNNaN1NaNNaNCo-operative Society600 sqftNaNNaN
993 BHK Ready to Occupy Flat for sale in Pride Palms KolshetOne can find this stunning 3 BHK flat for sale in Kolshet, Thane. Ideally situated in the Pride Palms township it enjoys a prime location. This flat for resale is the perfect property for you! This ready to move flat located in Kolshet is available for purchase at a fair price of INR 1.60 Cr. The spacious apartment is unfurnished. This 3 BHK flat boasts of being in close proximity to significant landmarks like kalpataru that enhance the overall living experience.1.60 Cr11150.0thane900 sqftReady to Move3 out of 27ResaleUnfurnishedEastGarden/ParkPride Palms311 CoveredFreeholdNaNNaNNaN
IndexTitleDescriptionAmount(in rupees)Price (in rupees)locationCarpet AreaStatusFloorTransactionFurnishingfacingoverlookingSocietyBathroomBalconyCar ParkingOwnershipSuper AreaDimensionsPlot Area
1875211875214 BHK Ready to Occupy Flat for sale Nagla RoadNagla Road, Zirakpur has an appealing 4 BHK flat for sale with various amenities. This flat all equipped with required facilities, is up for resale. This ready to move flat in Nagla Road comes at an affordable price of INR 1.18 Cr. It is unfurnished to accommodate your needs.1.18 Cr5816.0zirakpurNaNReady to Move2 out of 11ResaleUnfurnishedNaNGarden/Park, Main RoadNaN44NaNFreehold2029 sqftNaNNaN
1875221875223 BHK Ready to Occupy Flat for sale in GHB Splande Patiala RoadUp for immediate sale is a 3 BHK apartment in Patiala Road, Zirakpur. Don't miss this bargain flat for sale. It enjoys an excellent location within the Ghb Splande. This flat all equipped with required facilities, is up for resale. This ready to move flat in Patiala Road can be taken at a very economical pricing of INR 80 Lac. The flat is semi-furnished and makes for an ideal choice for any family. This 3 BHK flat boasts of being in close proximity to significant landmarks like chimney gardens that enhance the overall living experience.80 Lac4040.0zirakpur1200 sqftReady to Move3 out of 3ResaleSemi-FurnishedEastGarden/ParkGHB Splande33NaNFreeholdNaNNaNNaN
1875231875235 BHK Ready to Occupy Flat for sale in Orvis Grand ZIRAKPURThis magnificent 5 BHK Flat is available for sale in ZIRAKPUR, Zirakpur. It is in a prime location within the Orvis Grand. This apartment is a property of choice for resale. This ready to move flat in ZIRAKPUR can be availed at a reasonable price of INR 1.19 Cr. This contemporary apartment is semi-furnished. old ambala kalka highway nearby delhi public bird school , zirakpur are some major landmarks near the apartment.1.19 Cr4547.0zirakpur1705 sqftReady to Move5 out of 10ResaleSemi-FurnishedNorth - EastGarden/Park, Pool, Main RoadOrvis Grand531 CoveredFreeholdNaNNaNNaN
1875241875243 BHK Ready to Occupy Flat for sale in Sushma Joynest MOH 1 Airport RoadOne can find this stunning 3 BHK flat for sale in Airport Road, Zirakpur. Well-tucked in the Sushma Joynest Moh 1 township, the property is easily accessible. Your search ends here, because this flat for resale is among the best bargains in town. Available at a reasonable selling price of INR 69.6 Lac, this ready to move apartment in Airport Road is a great buy. The spacious apartment is semi-furnished. Some nearby landmarks are pr7 airport road, zirakpur.69.6 Lac5135.0zirakpur895 sqftReady to Move5 out of 8ResaleSemi-FurnishedNorth - EastGarden/Park, Pool, Main RoadSushma Joynest MOH 1321 CoveredFreeholdNaNNaNNaN
1875251875253 BHK Ready to Occupy Flat for sale in Peer Muchalla Apartments RWF Peer MuchallaHave a look at this immaculate 3 BHK flat for sale in Peer Muchalla, Zirakpur. Located in the Peer Muchalla Apartments Rwf township, the flat enjoys access to the prime spots in the city. This is a desirable apartment for sale. This ready to move flat located in Peer Muchalla is available for purchase at a fair price of INR 44.9 Lac. The flat is uniquely designed to enhance the living style. It is unfurnished, studded with all the basic facilities. near buali sahib gurudwara are some of the well-known landmarks in this locality.44.9 Lac3904.0zirakpur1050 sqftReady to Move1 out of 3New PropertyUnfurnishedNorth - EastGarden/Park, Main RoadPeer Muchalla Apartments RWF32NaNFreeholdNaNNaNNaN
1875261875263 BHK Ready to Occupy Flat for sale in Bollywood Esencia GazipurThis magnificent 3 BHK Flat is available for sale in Gazipur, Zirakpur. Located in the Bollywood Esencia township, the flat enjoys access to the prime spots in the city. This flat for sale is the perfect property for you! This ready to move flat in Gazipur can be taken at a very economical pricing of INR 63 Lac. Available in semi-furnished state, this flat is a great buy. Prominent landmarks in and around this locality are this property is located on gazipur road near nh, zirakpur.63 Lac3225.0zirakpurNaNReady to Move2 out of 4New PropertySemi-FurnishedEastGarden/ParkBollywood Esencia331 CoveredFreehold1953 sqftNaNNaN
1875271875273 BHK Ready to Occupy Flat for sale in Sushma Urban Views ZIRAKPURHave a look at this immaculate 3 BHK flat for sale in ZIRAKPUR, Zirakpur. It is based at Sushma Urban Views complex, that occupies a prominent place in the locality. This apartment is a property of choice for resale. Available at a reasonable selling price of INR 55 Lac, this ready to move apartment in ZIRAKPUR is a great buy. This immaculate flat boasts of coming in unfurnished form which takes the entire deal to the next level.55 Lac3274.0zirakpurNaNReady to Move4 out of 6ResaleUnfurnishedNorth - EastGarden/Park, Main RoadSushma Urban Views3NaN1 CoveredNaN1680 sqftNaNNaN
1875281875283 BHK Ready to Occupy Flat for sale in Bollywood Esencia GazipurGazipur, Zirakpur has an appealing 3 BHK flat for sale with various amenities. This flat is placed in a marvellous location within the Bollywood Esencia complex. This flat is available as a resale property. This ready to move flat in Gazipur can be availed at a reasonable price of INR 76 Lac. This flat is an ideal choice because it is an furnished apartment with all basic amenities. Significant landmarks in its proximity are this property is available on gajipur road..76 Lac4343.0zirakpur1250 sqftReady to Move1 out of 3ResaleFurnishedEastGarden/Park, Main RoadBollywood Esencia321 Covered,FreeholdNaNNaNNaN
1875291875292 BHK Ready to Occupy Flat for sale in Friends Enclave KishanpuraUp for immediate sale is a 2 BHK apartment in Kishanpura, Zirakpur. Don't miss this bargain flat for sale. This flat is placed in a marvellous location within the Friends Enclave complex. This premium flat is available for resale at an unbelievable price, so, grab it before it's gone! This ready to move flat in Kishanpura comes at an affordable price of INR 30 Lac. This premium semi-furnished flat spells quality and comfort at a competitive price.30 Lac4231.0zirakpurNaNReady to Move2 out of 2ResaleSemi-FurnishedNaNMain RoadFriends Enclave2NaNNaNNaN709 sqftNaNNaN
1875301875303 BHK Ready to Occupy Flat for sale in Affinity Greens Airport RoadThis exquisite 3 BHK Flat is offered for sale in Airport Road, Zirakpur. This flat is situated within the renown township of Affinity Greens. This flat for resale is a choice property. This ready to move flat in Airport Road comes at an affordable price of INR 1.18 Cr. The flat is semi-furnished and is suitable for any family size. this property is located on airport road, zirakpur are some major landmarks near the apartment.1.18 Cr6162.0zirakpurNaNReady to Move5 out of 13ResaleSemi-FurnishedNorth - EastGarden/Park, PoolAffinity Greens441 CoveredFreehold1915 sqftNaNNaN